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    Steady-State Anderson Accelerated Coupling of Lattice Boltzmann and Navier–Stokes Solvers

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    Type
    Article
    Authors
    Atanasov, Atanas
    Uekermann, Benjamin
    Pachajoa Mejía, Carlos
    Bungartz, Hans-Joachim
    Neumann, Philipp
    KAUST Grant Number
    UK-C0020
    Date
    2016-10-17
    Permanent link to this record
    http://hdl.handle.net/10754/623597
    
    Metadata
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    Abstract
    We present an Anderson acceleration-based approach to spatially couple three-dimensional Lattice Boltzmann and Navier–Stokes (LBNS) flow simulations. This allows to locally exploit the computational features of both fluid flow solver approaches to the fullest extent and yields enhanced control to match the LB and NS degrees of freedom within the LBNS overlap layer. Designed for parallel Schwarz coupling, the Anderson acceleration allows for the simultaneous execution of both Lattice Boltzmann and Navier–Stokes solver. We detail our coupling methodology, validate it, and study convergence and accuracy of the Anderson accelerated coupling, considering three steady-state scenarios: plane channel flow, flow around a sphere and channel flow across a porous structure. We find that the Anderson accelerated coupling yields a speed-up (in terms of iteration steps) of up to 40% in the considered scenarios, compared to strictly sequential Schwarz coupling.
    Citation
    Atanasov A, Uekermann B, Pachajoa Mejía C, Bungartz H-J, Neumann P (2016) Steady-State Anderson Accelerated Coupling of Lattice Boltzmann and Navier–Stokes Solvers. Computation 4: 38. Available: http://dx.doi.org/10.3390/computation4040038.
    Sponsors
    This work was partially supported by the Award No. UK-C0020 made by King Abdullah University of Science and Technology (KAUST), and by the priority program “1648 Software for Exascale Computing” of the German Research Foundation (DFG). The financial support of the Institute for Advanced Study (IAS) of the Technical University of Munich is acknlowedged. We further thank the Munich Centre of Advanced Computing (MAC) for providing computational resources.
    Publisher
    MDPI AG
    Journal
    Computation
    DOI
    10.3390/computation4040038
    ae974a485f413a2113503eed53cd6c53
    10.3390/computation4040038
    Scopus Count
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